Yiming Ying - RankMe

120 papers A* 27A 5B 4C 2Journal 71Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Optimization and Generalization of Gradient Descent for Shallow ReLU Networks with Minimal Width. J. Mach. Learn. Res. Yunwen Lei, Puyu Wang, Yiming Ying, Ding-Xuan Zhou
2026	J	`jnl`	i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splatting. CoRR Yicheng Cao, Zhuo Huang, Yu Yao, Yiming Ying, Daoyi Dong, Tongliang Liu
2025	J	`jnl`	Generalization Guarantees of Gradient Descent for Shallow Neural Networks. Neural Comput. Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou
2025	A*	`conf`	How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality Reduction. ICML Jun Chen, Hong Chen, Yonghua Yu, Yiming Ying
2025	J	`jnl`	How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality Reduction. CoRR Jun Chen, Hong Chen, Yonghua Yu, Yiming Ying
2025	A*	`conf`	On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. ICLR Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang
2025	J	`jnl`	Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification. CoRR Yuanfan Li, Yunwen Lei, Zheng-Chu Guo, Yiming Ying
2025	B	`conf`	Optimal Utility Bounds for Differentially Private Gradient Descent in Three-Layer Neural Networks. DSAA Puyu Wang, Yunwen Lei, Marius Kloft, Yiming Ying
2024	J	`jnl`	Differentially private stochastic gradient descent with low-noise. Neurocomputing Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2024	J	`jnl`	On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. CoRR Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang
2024	A*	`conf`	Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms. ICML Ming Yang, Xiyuan Wei, Tianbao Yang, Yiming Ying
2024	J	`jnl`	Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. J. Mach. Learn. Res. Lisha Chen, Heshan Devaka Fernando, Yiming Ying, Tianyi Chen
2023	J	`jnl`	AUC Maximization in the Era of Big Data and AI: A Survey. ACM Comput. Surv. Tianbao Yang, Yiming Ying
2023	J	`jnl`	Differentially Private Non-convex Learning for Multi-layer Neural Networks. CoRR Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying, Di Wang
2023	—	`conf`	Fairness-aware Differentially Private Collaborative Filtering. WWW (Companion Volume) Zhenhuan Yang, Yingqiang Ge, Congzhe Su, Dingxian Wang, Xiaoting Zhao, Yiming Ying
2023	J	`jnl`	Fairness-aware Differentially Private Collaborative Filtering. CoRR Zhenhuan Yang, Yingqiang Ge, Congzhe Su, Dingxian Wang, Xiaoting Zhao, Yiming Ying
2023	A*	`conf`	Generalization Analysis for Contrastive Representation Learning. ICML Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
2023	J	`jnl`	Generalization Analysis for Contrastive Representation Learning. CoRR Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou
2023	J	`jnl`	Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou
2023	A*	`conf`	Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity. ICML Dixian Zhu, Yiming Ying, Tianbao Yang
2023	J	`jnl`	Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning. J. Mach. Learn. Res. Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
2023	A*	`conf`	Minimax AUC Fairness: Efficient Algorithm with Provable Convergence. AAAI Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney, Yiming Ying
2023	C	`conf`	Outlier Robust Adversarial Training. ACML Shu Hu, Zhenhuan Yang, Xin Wang, Yiming Ying, Siwei Lyu
2023	J	`jnl`	Outlier Robust Adversarial Training. CoRR Shu Hu, Zhenhuan Yang, Xin Wang, Yiming Ying, Siwei Lyu
2023	J	`jnl`	Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms. CoRR Ming Yang, Xiyuan Wei, Tianbao Yang, Yiming Ying
2023	A*	`conf`	Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. NeurIPS Lisha Chen, Heshan Devaka Fernando, Yiming Ying, Tianyi Chen
2023	J	`jnl`	Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. CoRR Lisha Chen, Heshan Devaka Fernando, Yiming Ying, Tianyi Chen
2023	J	`jnl`	Unmixing biological fluorescence image data with sparse and low-rank Poisson regression. Bioinform. Ruogu Wang, Alex A. Lemus, Colin M. Henneberry, Yiming Ying, Yunlong Feng, Alex M. Valm
2022	J	`jnl`	AUC Maximization in the Era of Big Data and AI: A Survey. CoRR Tianbao Yang, Yiming Ying
2022	J	`jnl`	Average Top-k Aggregate Loss for Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. Siwei Lyu, Yanbo Fan, Yiming Ying, Bao-Gang Hu
2022	—	`conf`	Circular Capacitive Coupler for Stable Output Under Horizontal Misalignment. ISIE Heyuan Li, Yipeng Liu, Yiming Ying, Minfan Fu
2022	J	`jnl`	Differentially Private SGDA for Minimax Problems. CoRR Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
2022	J	`jnl`	Differentially Private Stochastic Gradient Descent with Low-Noise. CoRR Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2022	A	`conf`	Differentially private SGDA for minimax problems. UAI Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying
2022	J	`jnl`	Minimax AUC Fairness: Efficient Algorithm with Provable Convergence. CoRR Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney, Yiming Ying
2022	A*	`conf`	Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. NeurIPS Yunwen Lei, Rong Jin, Yiming Ying
2022	J	`jnl`	Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. CoRR Yunwen Lei, Rong Jin, Yiming Ying
2022	A*	`conf`	Stability and Generalization for Markov Chain Stochastic Gradient Methods. NeurIPS Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2022	J	`jnl`	Stability and Generalization for Markov Chain Stochastic Gradient Methods. CoRR Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou
2022	J	`jnl`	Sum of Ranked Range Loss for Supervised Learning. J. Mach. Learn. Res. Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
2022	J	`jnl`	Time Series Anomaly Detection for Trustworthy Services in Cloud Computing Systems. IEEE Trans. Big Data Chengqiang Huang, Geyong Min, Yulei Wu, Yiming Ying, Ke Pei, Zuochang Xiang
2021	J	`jnl`	Differentially Private SGD with Non-Smooth Loss. CoRR Puyu Wang, Yunwen Lei, Yiming Ying, Hai Zhang
2021	J	`jnl`	Differentially private empirical risk minimization for AUC maximization. Neurocomputing Puyu Wang, Zhenhuan Yang, Yunwen Lei, Yiming Ying, Hai Zhang
2021	A	`conf`	Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning. AISTATS Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu
2021	A*	`conf`	Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity. ICML Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
2021	J	`jnl`	Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity. CoRR Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
2021	A*	`conf`	Generalization Guarantee of SGD for Pairwise Learning. NeurIPS Yunwen Lei, Mingrui Liu, Yiming Ying
2021	J	`jnl`	Memory-based Optimization Methods for Model-Agnostic Meta-Learning. CoRR Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
2021	A*	`conf`	Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions. ICLR Yunwen Lei, Yiming Ying
2021	A*	`conf`	Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. NeurIPS Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
2021	J	`jnl`	Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning. CoRR Zhenhuan Yang, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
2021	A	`conf`	Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss. AISTATS Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying
2021	A*	`conf`	Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. ICML Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
2021	J	`jnl`	Stability and Generalization of Stochastic Gradient Methods for Minimax Problems. CoRR Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
2021	J	`jnl`	Stochastic Proximal AUC Maximization. J. Mach. Learn. Res. Yunwen Lei, Yiming Ying
2021	J	`jnl`	Sum of Ranked Range Loss for Supervised Learning. CoRR Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
2020	A*	`conf`	Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. ICML Yunwen Lei, Yiming Ying
2020	J	`jnl`	Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent. CoRR Yunwen Lei, Yiming Ying
2020	A*	`conf`	Learning by Minimizing the Sum of Ranked Range. NeurIPS Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
2020	J	`jnl`	Learning by Minimizing the Sum of Ranked Range. CoRR Shu Hu, Yiming Ying, Xin Wang, Siwei Lyu
2020	A*	`conf`	Online AUC Optimization for Sparse High-Dimensional Datasets. ICDM Baojian Zhou, Yiming Ying, Steven Skiena
2020	J	`jnl`	Online AUC Optimization for Sparse High-Dimensional Datasets. CoRR Baojian Zhou, Yiming Ying, Steven Skiena
2020	A*	`conf`	Stochastic AUC Maximization with Deep Neural Networks. ICLR Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang
2020	A*	`conf`	Stochastic Hard Thresholding Algorithms for AUC Maximization. ICDM Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
2020	J	`jnl`	Stochastic Hard Thresholding Algorithms for AUC Maximization. CoRR Zhenhuan Yang, Baojian Zhou, Yunwen Lei, Yiming Ying
2019	A*	`conf`	Dual Averaging Method for Online Graph-structured Sparsity. KDD Baojian Zhou, Feng Chen, Yiming Ying
2019	J	`jnl`	Dual Averaging Method for Online Graph-structured Sparsity. CoRR Baojian Zhou, Feng Chen, Yiming Ying
2019	J	`jnl`	Online optimization for residential PV-ESS energy system scheduling. Math. Found. Comput. Zhenhuan Yang, Yiming Ying, Qilong Min
2019	J	`jnl`	Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning. CoRR Wei Shen, Zhenhuan Yang, Yiming Ying, Xiaoming Yuan
2019	J	`jnl`	Stochastic AUC Maximization with Deep Neural Networks. CoRR Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang
2019	J	`jnl`	Stochastic AUC Optimization Algorithms With Linear Convergence. Frontiers Appl. Math. Stat. Michael Natole, Yiming Ying, Siwei Lyu
2019	A*	`conf`	Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization. ICML Baojian Zhou, Feng Chen, Yiming Ying
2019	J	`jnl`	Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization. CoRR Baojian Zhou, Feng Chen, Yiming Ying
2019	J	`jnl`	Stochastic Proximal AUC Maximization. CoRR Yunwen Lei, Yiming Ying
2018	A	`conf`	A Univariate Bound of Area Under ROC. UAI Siwei Lyu, Yiming Ying
2018	B	`conf`	Explain Black-box Image Classifications Using Superpixel-based Interpretation. ICPR Yi Wei, Ming-Ching Chang, Yiming Ying, Ser Nam Lim, Siwei Lyu
2018	B	`conf`	Kernelized Convex Hull Approximation and its Applications in Data Description Tasks. IJCNN Chengqiang Huang, Yulei Wu, Geyong Min, Yiming Ying
2018	J	`jnl`	Learning local metrics from pairwise similarity data. Pattern Recognit. Julien Bohné, Yiming Ying, Stéphane Gentric, Massimiliano Pontil
2018	J	`jnl`	Learning with Correntropy-induced Losses for Regression with Mixture of Symmetric Stable Noise. CoRR Yunlong Feng, Yiming Ying
2018	A*	`conf`	Stochastic Proximal Algorithms for AUC Maximization. ICML Michael Natole, Yiming Ying, Siwei Lyu
2018	J	`jnl`	Supervised Intra- and Inter-Modality Similarity Preserving Hashing for Cross-Modal Retrieval. IEEE Access Zhikui Chen, Fangming Zhong, Geyong Min, Yonglin Leng, Yiming Ying
2017	—	`conf`	Learning with Average Top-k Loss. NIPS Yanbo Fan, Siwei Lyu, Yiming Ying, Bao-Gang Hu
2017	J	`jnl`	Learning with Average Top-k Loss. CoRR Yanbo Fan, Siwei Lyu, Yiming Ying, Bao-Gang Hu
2017	J	`jnl`	Online regularized learning with pairwise loss functions. Adv. Comput. Math. Zheng-Chu Guo, Yiming Ying, Ding-Xuan Zhou
2016	A*	`conf`	Co-Regularized PLSA for Multi-Modal Learning. AAAI Xin Wang, Ming-Ching Chang, Yiming Ying, Siwei Lyu
2016	A	`conf`	Fast Convergence of Online Pairwise Learning Algorithms. AISTATS Martin Boissier, Siwei Lyu, Yiming Ying, Ding-Xuan Zhou
2016	J	`jnl`	Generalization bounds for metric and similarity learning. Mach. Learn. Qiong Cao, Zheng-Chu Guo, Yiming Ying
2016	J	`jnl`	Online Pairwise Learning Algorithms. Neural Comput. Yiming Ying, Ding-Xuan Zhou
2016	—	`conf`	Stochastic Online AUC Maximization. NIPS Yiming Ying, Longyin Wen, Siwei Lyu
2015	J	`jnl`	Online Pairwise Learning Algorithms with Kernels. CoRR Yiming Ying, Ding-Xuan Zhou
2015	J	`jnl`	Unregularized Online Learning Algorithms with General Loss Functions. CoRR Yiming Ying, Ding-Xuan Zhou
2014	J	`jnl`	Guaranteed Classification via Regularized Similarity Learning. Neural Comput. Zheng-Chu Guo, Yiming Ying
2014	—	`conf`	Large Margin Local Metric Learning. ECCV (2) Julien Bohné, Yiming Ying, Stéphane Gentric, Massimiliano Pontil
2013	J	`jnl`	Guaranteed Classification via Regularized Similarity Learning. CoRR Zheng-Chu Guo, Yiming Ying
2013	A*	`conf`	Similarity Metric Learning for Face Recognition. ICCV Qiong Cao, Yiming Ying, Peng Li
2012	—	`conf`	Distance Metric Learning Revisited. ECML/PKDD (1) Qiong Cao, Yiming Ying, Peng Li
2012	J	`jnl`	Distance Metric Learning with Eigenvalue Optimization. J. Mach. Learn. Res. Yiming Ying, Peng Li
2012	J	`jnl`	Generalization Bounds for Metric and Similarity Learning CoRR Qiong Cao, Zheng-Chu Guo, Yiming Ying
2012	J	`jnl`	Learning the coordinate gradients. Adv. Comput. Math. Yiming Ying, Qiang Wu, Colin Campbell
2011	J	`jnl`	Generalized sparse metric learning with relative comparisons. Knowl. Inf. Syst. Kaizhu Huang, Yiming Ying, Colin Campbell
2011	—	`book`	Learning with Support Vector Machines Colin Campbell, Yiming Ying
2010	J	`jnl`	Rademacher Chaos Complexities for Learning the Kernel Problem. Neural Comput. Yiming Ying, Colin Campbell
2009	B	`conf`	A Variational Approach to Semi-Supervised Clustering. ESANN Peng Li, Yiming Ying, Colin Campbell
2009	—	`conf`	Analysis of SVM with Indefinite Kernels. NIPS Yiming Ying, Colin Campbell, Mark A. Girolami
2009	—	`conf`	Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami
2009	J	`jnl`	Enhanced protein fold recognition through a novel data integration approach. BMC Bioinform. Yiming Ying, Kaizhu Huang, Colin Campbell
2009	A*	`conf`	GSML: A Unified Framework for Sparse Metric Learning. ICDM Kaizhu Huang, Yiming Ying, Colin Campbell
2009	A*	`conf`	Generalization Bounds for Learning the Kernel Problem. COLT Yiming Ying, Colin Campbell
2009	—	`conf`	Sparse Metric Learning via Smooth Optimization. NIPS Yiming Ying, Kaizhu Huang, Colin Campbell
2008	C	`conf`	Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. ICMLA Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell
2008	A*	`conf`	Learning Coordinate Gradients with Multi-Task Kernels. COLT Yiming Ying, Colin Campbell
2008	J	`jnl`	Online Gradient Descent Learning Algorithms. Found. Comput. Math. Yiming Ying, Massimiliano Pontil
2008	J	`jnl`	Universal Multi-Task Kernels. J. Mach. Learn. Res. Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying
2007	—	`conf`	A Spectral Regularization Framework for Multi-Task Structure Learning. NIPS Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying
2007	J	`jnl`	Convergence analysis of online algorithms. Adv. Comput. Math. Yiming Ying
2007	J	`jnl`	Learnability of Gaussians with Flexible Variances. J. Mach. Learn. Res. Yiming Ying, Ding-Xuan Zhou
2007	J	`jnl`	Multi-kernel regularized classifiers. J. Complex. Qiang Wu, Yiming Ying, Ding-Xuan Zhou
2006	J	`jnl`	Learning Rates of Least-Square Regularized Regression. Found. Comput. Math. Qiang Wu, Yiming Ying, Ding-Xuan Zhou
2006	J	`jnl`	Online Regularized Classification Algorithms. IEEE Trans. Inf. Theory Yiming Ying, Ding-Xuan Zhou
2004	J	`jnl`	Support Vector Machine Soft Margin Classifiers: Error Analysis. J. Mach. Learn. Res. Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou